Mads Ipsen wrote:

> Hi,
> 
> Sorry if this is a double post - unsure if it made it the first time:
> 
> Here are some timings that puzzle me a bit. Sum the two rows of a 2xn
> matrix, where n is some large number
> 
> python -m timeit -s "from numpy import array,sum,reshape; x =
> array([1.5]*1000); x = reshape(x,(2,500))" "x.sum(0)"
> 10000 loops, best of 3: 36.2 usec per loop
> 
> python -m timeit -s "from numpy import array,sum,reshape; x =
> array([1.5]*1000); x = reshape(x,(2,500))" "x[0] + x[1]"
> 100000 loops, best of 3: 5.35 usec per loop
>   
> 

This is probably reasonable.  There is overhead in the looping construct 
(basically what happens is that the first element is copied into the 
output and then a function called --- which in this case has a loop of 
size 1 to compute the sum).   

This is then repeated 500 times.  So, you have 500 C-function pointer 
calls in the first case.
In the second case you have basically a single call to the same function 
where the 500-element loop is done.

I'm a little surprised that Numeric is so much faster for this case as 
you show later.   The sum code is actually add.reduce... which uses a 
generic reduction concept in ufuncs.  It has overhead over what you 
might do using some less general approach.

If anyone can figure out how to make the NOBUFFER secion in 
GenericReduce faster in ufuncobject.c it will be greatly welcomed.

Speed improvements are always welcome.

-Travis




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